Director, Data Platform & Integration Engineering Lead

Work Location:

New York, New York, United States of America

Hours

40

Line Of Business

Technology Solutions

Pay Detail

$220,000 - $260,000 USD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description

Preferred Qualifications:

Role Overview

The Director, Data Platform & Integration Engineering Lead owns the engineering strategy and delivery of shared data platforms and integration capabilities for TDS AI & Data Technology: strategic data platforms and lakehouse, processing frameworks and self-service, data ingestion, streaming and events, and metadata, connectivity and shared pipelines.

The role brings platform engineering, data integration and data architecture into one accountable capability, and requires hands-on technical depth, engineering leadership, product thinking and commercial judgment.

What You’ll Do

• Set platform and integration strategy. Define the multiyear target architecture and roadmap; set standards and reference architectures; decide where to build, buy, consolidate or retire; rationalize duplicated platforms and pipelines.
• Lead data-platform engineering. Lead lakehouse and warehouse engineering on Databricks, Snowflake or equivalent; provide reusable processing frameworks and self-service so domain data-product teams do not rebuild foundations.
• Modernize integration and streaming. Lead batch, real-time, event-driven and API integration; set Kafka and Flink standards; define when to move, stream, virtualize (Dremio, Starburst, Denodo) or query data in place.
• Set software-engineering standards. Apply Python, Java, Spring Boot, API, CI/CD, DevSecOps and infrastructure-as-code practices; run pipelines and platforms as production software.
• Embed governance and controls. Build metadata, lineage, quality and policy enforcement into the platform (Collibra, Unity Catalog); partner with the CDO organization to automate controls and data contracts.
• Enable analytics consumption. Establish patterns for Sigma, Strategy and Power BI on governed data products with shared semantics, and rationalize overlapping BI tooling.
• Operate platforms as products and lead people. Own roadmaps, SLOs, reliability, cost and TCO; lead engineering managers, architects and engineers; manage strategic vendors; build succession.

What You Bring

• Deep experience engineering modern enterprise data platforms: lakehouse, warehouse, distributed query, streaming and data processing. Databricks and/or Snowflake strongly preferred.
• Working knowledge of Kafka, Flink, data virtualization (Dremio, Starburst, Denodo) and governance tooling (Collibra, Unity Catalog).
• Proficiency in Python,...

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